Some vision-based occupant sensing systems have implemented dual cameras to perform optical triangulation ranging. However, such systems with dual cameras tend to be slow and expensive and generally have poor distance measurement accuracy, when an object to be ranged lacks surface texture. Other vision-based occupant sensing systems have implemented a single camera and temporally encoded probing beams for triangulation ranging. In those systems, the probing beams are sequentially directed to different parts of the object through beam scanning or control of light source arrays. However, such systems are generally not suitable for high volume production and/or are limited in spatial resolution. In general, as such systems measure distance one point at a time, fast two-dimensional (2D) ranging cannot be achieved unless an expensive high-speed camera is used.
A difficulty with using a single camera and simultaneously projected probing beams for triangulation is distinguishing each individual beam image from the rest of the beam images in the image plane. As the target distance is measured through the correlation between the distance of the target upon which the beam is projected and the location of the returned beam image in the image plane, each individual beam image must be distinguished to accurately profile a given target. However, when multiple beam images are simultaneously projected, one particular location on the image plane may be correlated with several beam images with different target distances. In order to measure distance correctly, each beam image must be labeled without ambiguity.
Various approaches have been implemented or contemplated to accurately locate and label beams of a beam matrix. For example, manually locating and labeling beams has been employed during calibration. However, manual locating and labeling beams is typically impractical in high volume production environments and is also error prone.
Another beam locating and labeling approach is based on the assumption that valid beams in a beam matrix are always brighter than those beams outside the matrix and the entire beam matrix is present in the image. However, this assumption creates strong limitations on a beam matrix projector and the sensing range of the system. Further, due to the imperfection of most projectors, it has been observed that some image noises can be locally brighter than some true beams. Further, desired sensing ranges for many applications result in partial images of the beam matrix being available.
In at least one vision-based occupant sensing system an additional diffused light source, e.g., a light emitting diode (LED), has been used in conjunction with a light projector or structured light source to enhance the acquisition of occupant images by a camera. In a typical vision-based occupant sensing system, two consecutive frames are generally required to accurately obtain range and image information. A first frame of image information is usually captured with both the diffused light source and the structured light source providing target illumination. A second frame is then captured with only the diffused light source providing target illumination. The difference of the two frames allows for the extraction of the structured probing beams (for range measurement). In this manner, the combination of the 2D images and the range profiles provides three-dimensional (3D) occupant information that can be used in various automotive applications, e.g., occupant classification in airbag safety applications.
When the diffused light source remains at a constant illumination, the image intensities captured by the camera can be significantly affected by many factors, such as changes in object reflectance, target distance and ambient light. For limited dynamic range and sensitivity of the system, a large variation of lighting conditions can cause dim or saturated images that lead to difficulties for accurate occupant classification. Such a system also requires that the camera be capable of registering the illumination provided by the diffused light source and the structured light system at the same time. Since the beam characteristics of the structured light (collimated) and the LED illumination (diffused) are very different, the contributions of the two light sources to the image strongly depend on the target distance.
What is needed is an occupant sensing system that is capable of adapting to varying lighting conditions.